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docs: fix typos (#1665)

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* docs: fix typos

* typos: fix typos found by `codespell` across the codebase

* docs: fix `macOS` spelling

* docs: fix `authentification` terminology

"Authentification" is not a thing.

* docs: fix `localhost` typo in example link

* typos: fix in-code typos

These are potentially higher risk, but no other mentions of these typos
show up in the codebase.
This commit is contained in:
Ben Boeckel
2022-09-25 23:17:27 +00:00
committed by GitHub
parent 33dad80eff
commit 2e6b877ba9
46 changed files with 66 additions and 66 deletions
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4
docs/docs/contributors/developers-guide/starting-dev-server.md
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@@ -36,7 +36,7 @@ Checkout the makefile for all of the available commands.
Once the prerequisites are installed you can cd into the project base directory and run `make setup` to install the python and node dependencies.
=== "Linux / MacOs"
=== "Linux / macOS"
```bash
# Naviate To The Root Directory
@@ -66,7 +66,7 @@ Before you start the server you MUST copy the `template.env` and `frontend/templ
Once that is complete you're ready to start the servers. You'll need two shells open, One for the server and one for the frontend.
=== "Linux / MacOs"
=== "Linux / macOS"
```bash
# Terminal #1

2
docs/docs/contributors/guides/ingredient-parser.md
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@@ -4,7 +4,7 @@ Mealie uses Conditional Random Fields (CRFs) for parsing and processing ingredie
## Improving The CRF Parser
To improve results with the model, you'll likely need to focus on improving the tokenization and parsing of the original string to aid the model in determine what the ingredient is. Datascience is not my forte, but I have done some tokenization to improve the model. You can find that code under `/mealie/services/parser_services/crfpp` along with some other utility functions to aid in the tokenization and processing of ingredient strings.
To improve results with the model, you'll likely need to focus on improving the tokenization and parsing of the original string to aid the model in determine what the ingredient is. Data science is not my forte, but I have done some tokenization to improve the model. You can find that code under `/mealie/services/parser_services/crfpp` along with some other utility functions to aid in the tokenization and processing of ingredient strings.
The best way to test on improving the parser is to register additional test cases in `/mealie/tests/unit_tests/test_crfpp_parser.py` and run the test after making changes to the tokenizer. Note that the test cases DO NOT run in the CI environment, therefore you will need to have CRF++ installed on your machine. If you're using a Mac the easiest way to do this is through brew.